摘要
应用大数据平台深入挖掘计量数据对配电网的运行支撑是当前电网重要研究方向,文中应用支持向量机(SVM)算法研究中压配网停电事件补全方法,解决停电事件准确统计难题。首先总结中压配电网的5类停电事件,接着重点研究了SVM补全方法,给出停电事件补全思路,5类停电事件的SVM补全模型构建方法,并提出了涵盖配电网模型构建、SVM模型构建、SVM求解及故障类型判断的补全流程,然后从工程应用角度,设计了补全模块与用电信息采集等各相关系统间的业务关系框架并进行数据分析架构设计。最后以安徽黄山等4家地市公司为例进行了实践应用分析,验证了文中研究方法可极大提升停电事件统计的及时性和准确性。
Deeply research metering data with the big data analysis platform for the distribution network operation is one of the key research directions in the power grid currently.Power outage event completion method based on SVM algorithm to solve accurate statistical problems for MV distribution network was researched in this paper.Firstly,based on summarizing the five types of power outages in the MV distribution network,the SVM completion method is mainly researched.And the power outage event completion idea based on SVM and a full-process of SVM completion model construction method for the five types of power outage events are given.Besides,the completion process of distribution network model construction,vector machine SVM construction,vector machine SVM solution and judgment of fault type are proposed.Then,the business relationship framework among the complementary modules and other related systems,the data analysis architecture based on the big data platform are designed from the perspective of engineering application.Finally,take the application of Anhui Huangshan and other three cities as an example,it verifies that the completion method can greatly improve the timeliness and accuracy of power failure event collection.
作者
张波
肖坚红
梁晓伟
疏奇奇
张良
隋仕伟
ZHANG Bo;XIAO Jianhong;LIANG Xiaowei;SHU Qiqi;ZHANG Liang;SUI Shiwei(Anhui Electric Power Co.,Ltd.,Hefei 230022,China;State Grid Anhui Electric Power Co.,Ltd.Research Institute,Hefei 230601,China;NARI Technology Co.,Ltd.,Nanjing 211106,China)
出处
《电力工程技术》
2019年第3期34-40,共7页
Electric Power Engineering Technology
基金
国家重点研发计划资助项目(2016YFB0901100)
国家电网有限公司总部科技项目“基于大数据技术的智能采集实时分析与辅助决策功能优化完善研究”
关键词
中压配电网
停电补全
大数据平台
支持向量机
停电事件完整率
medium voltage(MV)distribution network
power outage completion
big data analysis platform
support vector machine(SVM)
the power outage event completion rate
